Skip to main content
Glama

Mime

by io.github.pipeworx-io

Polymarket Arbitrage

polymarket_arbitrage
Read-onlyIdempotent

Find arbitrage opportunities on Polymarket via monotonicity violations + partition-sum checks. Call with NO args for a trending_scan of the top ~200 markets by weekly volume; pass event for the strongest per-event partition_check, or topic for a themed cross-event scan. event (recommended for a specific market): pass a Polymarket event slug like "fed-decision-may-2026" or "when-will-bitcoin-hit-150k"; walks child markets, checks date-axis / threshold-axis ordering AND computes the partition_check (sum of YES prices across mutually-exclusive legs — should ≈1; deviations >3pp emit a BUY/SELL EVERY LEG signal). topic (for cross-event scanning): pass a seed question like "Strait of Hormuz traffic returns to normal" or "Fed rate decision"; searches related events across the platform, flattens markets, runs the comparator on the union. Cross-event mode catches "...by May 31" vs "...by Jun 30" patterns that single-event misses. SEMANTIC ANCHOR: cross-event pairs require ≥0.30 Jaccard similarity on question tokens (prevents Powell-Fed-Pause being paired with Powell-DOJ-probe); skipped_low_similarity surfaces the rejected pair count. PARTITION FILTER: drops will-person-X / will-manager-Y / will-someone-else- placeholder slugs; partitions with >20% placeholder fraction return null arb signal. Response: opportunities[] (gap_pp, suggested_trade, reasoning, monotonicity violation context), and in event mode partition_check{sum_yes_prices, gap_from_1, placeholders_filtered, suggested_trade}. FILL CHECK: when the partition signal fires, arbitrage.fill_check prices it against live CLOB depth (theoretical_edge_pp_at_book vs realizable_edge_pp at 1000 shares/leg, thin_legs[]) — realizable_edge_pp ≤ 0 means the overround exists only at last-trade, not in the book; do not trade it. For custom sizing use polymarket_fill_risk.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
eventNoSingle-event mode (use this if you know the specific Polymarket event): event slug like "fed-decision-may-2026" or "when-will-bitcoin-hit-150k". Full Polymarket URLs also accepted.
topicNoCross-event mode (use this if you want to scan related events across the platform): a topic or seed question like "Fed rate decision" or "Strait of Hormuz traffic returns to normal". Tool searches Polymarket for related events and checks monotonicity across them.

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observed

TDQS

A4.9/5.0
Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations declare read-only, idempotent, non-destructive. The description adds extensive behavioral details: semantic anchor (Jaccard threshold), partition filter, fill check with book depth, and response structure, far exceeding annotation scope.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is verbose but well-structured: first sentence summarizes, then modes, then technical details. Every sentence adds value, though length could be trimmed for quicker parsing.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

No output schema, but description fully documents response fields, includes fill check logic, and references related tool (polymarket_fill_risk). Complete for the tool's complexity.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, but description adds rich meaning with examples ('fed-decision-may-2026'), explains mode behavior, and outlines the scanning logic, significantly enhancing understanding beyond the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool finds arbitrage opportunities via monotonicity violations and partition-sum checks, and distinguishes three modes (no args, event, topic) with specific behaviors, differentiating it from siblings like polymarket_edges.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicit guidance on when to use each parameter mode: 'Call with NO args for a trending_scan... pass event for... or topic for...' Includes examples and explains cross-event mode catches patterns single-event misses, providing clear context for selection.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

All Mime toolsInspect
Try in Browser
RayrunBuild, deploy, and operate MCP servers without becoming an infrastructure team.ray.runAd

Glama MCP Gateway

Add one secure layer between your agents and this server.

TDQS

A4/5.0
Disambiguation3/5

Several tools have overlapping purposes, such as the ask_pipeworx family (standard, beta, grounded) and the multiple Polymarket analysis tools (edges, arbitrage, fill_risk, edge_tracker, kalshi_spread, bet_research). The detailed descriptions help differentiate them, but an agent could still misselect between deep_research vs ask_pipeworx or polymarket_edges vs polymarket_arbitrage.

Naming Consistency3/5

Naming patterns are mixed: many tools use verb_noun (discover_tools, validate_claim, compare_entities), but others are noun_noun (entity_profile, polymarket_edges), single verbs (remember, recall, forget), or unusual forms (extension_for, search_within, ask_pipeworx). The polymarket_ prefix and ask_pipeworx family provide some consistency, but overall the style is not uniform.

Tool Count2/5

33 tools is a large number for the server's scope. While it covers many domains (data querying, entity research, Polymarket analysis, subscriptions, memory, utilities), there is redundancy: three ask_pipeworx variants and six Polymarket-specific tools inflate the count. Several tools could be merged or dropped without losing functionality, making the set feel heavier than necessary.

Completeness4/5

The toolset covers its core domains well: data querying (ask_pipeworx, deep_research), entity resolution (resolve_entity, entity_profile, compare_entities), Polymarket analysis (research, arbitrage, risk, edges, tracking, cross-venue), subscriptions (subscribe/unsubscribe/list/alerts), memory (remember/recall/forget), and utilities (MIME lookup, dependency scan). Minor gaps exist, such as no direct fetch tool for pipeworx:// citation URIs and no update operation for subscriptions, but these are not critical.

Resources